Stereo video for gaming

ABSTRACT

A real-time stereo video signal of a captured scene with a physical foreground object and a physical background is received. In real-time, a foreground/background separation algorithm is used on the real-time stereo video signal to identify pixels from the stereo video signal that represent the physical foreground object. A video sequence is produced by rendering a 3d virtual reality based on the identified pixels of the physical foreground object.

BACKGROUND

Three dimensional (3d) graphics, in particular, simulated 3d realms orworlds, sometimes called 3d virtual reality, is a well known area ofcomputer graphics, which typically involves rendering two dimensionalimages of 3d models and scenery in a 3d coordinate space. Most moderngame consoles are designed specifically to be able to process 3dgraphics in real-time, and many games for game consoles are based on asimulated 3d or virtual reality.

Game consoles are usually operated using game controllers, such asjoysticks, button pads, and so on. For many players, significant timemust be spent before a game control can be used proficiently. For lackof dexterity, many people do not regularly use a game console. Althoughgame consoles have become powerful and can process a high level ofcontrol input from a user, it is difficult to provide a high level ofcontrol input using typical game controllers such as a touchpads,joysticks, mice, etc. Furthermore, game controllers are often notphysically operated in a manner that meets a user's mental model orintuitive understanding of a game. In other words, a 3d game may involvecausing an avatar to run, jump, hold different objects, shoot, duck,etc., perhaps simultaneously. However, a game controller can usuallyonly output one or a few input signals at one time, and hands are notefficient at simultaneously controlling different types of actions, suchas simultaneously moving an avatar, picking up an object, aiming, and soon.

Game consoles have also been limited in the type of imagery that theydisplay. Typically, the graphics displayed by a game console aregenerated internally by a game or are provided in advance. For example,the images for animating a sprite may be part of a game's embeddedcontent or program data. Real-time captured video of objects has notbeen inserted or mapped into 3d virtual reality.

SUMMARY

The following summary is included only to introduce some conceptsdiscussed in the Detailed Description below. This summary is notcomprehensive and is not intended to delineate the scope of the claimedsubject matter, which is set forth by the claims presented at the end.

A real-time stereo video signal of a captured scene with a physicalforeground object and a physical background is received. In real-time, aforeground/background separation algorithm is used on the real-timestereo video signal to identify pixels from the stereo video signal thatrepresent the physical object. A video sequence is produced by renderinga 3d virtual reality based on the identified pixels of the physicalforeground object.

Many of the attendant features will be more readily appreciated byreferring to the following detailed description considered in connectionwith the accompanying drawings.

DESCRIPTION OF THE DRAWINGS

Like reference numerals are used to designate like parts in theaccompanying Drawings.

FIG. 1 shows a stereo camera connected to a game console.

FIG. 2 shows a high level system diagram of a game console configured tooperate in conjunction with a stereo camera.

FIG. 3 shows an example of a game console.

FIG. 4 shows another example game console.

FIG. 5 shows how information about a scene can be extracted from astereo video signal by device driver.

FIG. 6 shows how stereo-derived object information can be used inconjunction with a game and VR engine.

FIG. 7 shows an example of how stereo-based foreground/backgroundseparation can be used to control a model or avatar in a 3d game.

FIG. 8 shows a process for using stereo foreground/background separationto recognize gestures for controlling a game.

FIG. 9 shows an example of mapping a separated image of a foregroundobject to a model that is then rendered and displayed.

FIG. 10 shows how stereo-based object recognition can be used for 3dgaming.

DETAILED DESCRIPTION

Stereo cameras and algorithms for processing stereo video data haveprogressed to the point where it possible to reliably acquire certainimage information about captured objects in real time. A number ofpublications may be consulted. For example, “Bi-layer segmentation ofbinocular stereo video” (Vladimir Kolmogorov, Antonio Criminisi, AndrewBlake, Geoffrey Cross, Carsten Rother. 2005 San Diego, Calif., US Proc.IEEE Computer Vision and Pattern Recognition) discusses techniques forseparating foreground objects from their background by fusingcolor/contrast analysis with stereo pattern matching. Regarding basicstereo matching, see also Y. Ohta and T. Kanade, Stereo by intra- andinter-scan line search using dynamic programming, IEEE Trans. on PAMI,7(2), 1985; I. J. Cox, S. L. Hingorani, and S. B. Rao, A maximumlikelihood stereo algorithm, CVIU, 63(3):542-567, 1996; D. Scharsteinand R. Szeliski, A taxonomy and evaluation of dense two-frame stereocorrespondence algorithms, IJCV, 47(1-3), 2002. Regarding dealing withocclusion on object boundaries, see P. N. Belhumeur, A Bayesian-approachto binocular stereopsis, Int. J. Computer Vision, 19(3):237-260, August1996; D. Geiger, B. Ladendorf, and A. Yuille, Occlusions and binocularstereo, Int. J. Computer Vision, 14:211-226, 1995; and A. Criminisi, J.Shotton, A. Blake, and P. H. S. Torr, Gaze manipulation for one to oneteleconferencing, In Proc. ICCV, 2003.

In sum, stereo video processing algorithms can, in real time, accuratelyand robustly separate objects in the foreground of a captured scene fromthe background of the scene. A stereo camera signal can be processed toobtain information such as the depth or distance of an object from thecamera, the depth of pixels in an object's image, the identity of anobject, an image of the object with the background cleanly removedregardless of the background's color or distance, the orientation of anobject, and so on. In embodiments described below, information obtainedby processing a stereo video signal is used by a game console or 3dgraphics system.

FIG. 1 shows a stereo camera 50 connected to a game console 52. The gameconsole 52 is connected to a display 54. The stereo camera 50 capturesvideo of a real object 56 and a real person 58 holding the object 56.The captured stereo video includes any arbitrary background of thecaptured scene, for example, scenery, walls, distant objects such asfurniture, etc. In a preferred embodiment, the stereo camera 50 isplaced atop the television or display 54. In the arrangement shown inFIG. 1, the stereo camera 50 provides a stereo video signal of thecaptured video to the game console 52, which the game console 52processes to generate, for example, control information for controllinga game, graphics information to supplement the graphics of the game or3d virtual reality, 3d information about objects in the scene, etc. Forexample, as discussed later with reference to FIGS. 7-10, actions andappearances of the person 58 and/or object 56 can be translated intoactions and/or appearances in a 3d virtual reality rendered by the gameconsole 52.

FIG. 2 shows a high level system diagram of a game console 52 configuredto operate in conjunction with a stereo camera 50. In a preferredembodiment, the stereo camera 50 has at least two image capture devices70, such as a pair of CCDs. Low level capture and processing circuitry72 captures raw image data from the image capture devices 70. Thecircuitry 72 may perform some basic image processing functions on theraw image data, for example synchronization, frame rate adjustment,resizing, color balancing, contrast adjustment, and so on. The circuitry72 outputs a stream of stereo video, and the stereo camera'scommunication interface 74 passes the stereo video data to the computeror game console 52. The communication interface 74 can communicate withthe game console 52 using any form of physical communication, such asradio, electrical, or optical signals. In a preferred embodiment thecommunication interface 74 is a Universal Serial Bus (USB) interface.

The game console 52 receives the stereo video signal via an interface76. In a preferred embodiment, the stereo video signal is then processedby a special device driver 78. The device driver 78 performs imageprocessing on the stereo video signal to obtain information about thescene captured by the stereo video signal. Details of the special devicedriver 78 are discussed later. The device driver 78 is managed by anoperating system 80 (which may be embedded in the game console 52), andthe device driver 78 is invoked and used by an application program orgame 82.

The game 82 may use a 3d game engine 84. In a typical configuration,different games may share a common game engine 84. A game programtypically includes the content (models, animations, sounds, textures ortexture-generating procedures, and physics) and code that makes the gamework, such as artificial intelligence, game and control logic, etc. Gameengine 84 can be thought of as the software that is not specific to anyparticular game. A game engine typically performs functions such asrendering, storing models and scenes, lighting, shading, managingnetwork connections, detecting collisions, and more. The game engine 84generates frames for display.

The functionality of the device driver 78 may be accessed using aspecial application programming interface (API), with functions forperforming high-level operations such as: return a list of objectsseparated from the background; return the 3d position or orientation ofa particular separated object; return the identity of a particularseparated object, perhaps among a supplied list of candidates; returnthe 3d geometry of a particular foreground/background separated object(e.g. depths of pixels that correspond to the object); return an imageof a select object, the image having the background effectively removed;and others. Although a device driver is a convenient type of componentfor encapsulating stereo processing functionality, a device driver isnot required. Stereo processing can also be included as part of theoperating system 80, or as part of the game or application 82, or evenas a special hardware component of the game console 52. The game 82obtains the high-level image processing output of the device driver 78and uses it to help determine the behavior and/or appearance of thegame.

In a preferred embodiment, the stereo camera 50 is preferably anintegrated device where the image capture devices 70 share commoncircuitry and housing. Shared processing circuitry 72 allows stereovideo frames from the capture devices 70 to be easily paired andsynchronized, and the shared housing gives a fixed geometric relationbetween the image capture devices 70, which reduces the computationalcomplexity needed to analyze the stereo video signal. Nonetheless, apair of independent cameras can also be used, each outputting a videosignal and possibly with a connection to game console 52. In this case,some form of calibration and synchronization will usually be needed.

FIG. 3 shows an example of a game console 52. The individual componentsof example game console 100 are labeled and self-explanatory. FIG. 4shows another example game console 102. Another example of a gameconsole may be found in U.S. Patent Publication number 20020138637. Ascan be seen from these examples, a typical game console 52 has high endcomponents such as one or more CPUs, a GPU, memory, and high speedcommunication between the components.

FIG. 5 shows how information about a scene can be extracted from astereo video signal by device driver 78. The device driver 78 receives astream of stereo video, which is a stream of paired images, each from arespective image capture device 70. The images are sometimes referred toas left and right images. FIG. 5 shows a left image 120 and a rightimage 122. Although images 120, 122 appear identical in FIG. 5, pairedstereo images actually differ slightly due to the different position anddirection of their respective image capture devices. The difference ordisparity between two stereo images is computed and stored as adisparity map 124. The disparity map 124 is an array of pixel valueswhich represent the stereo disparity between the left and right images120, 122 at matching pixels. To generate the disparity values of thedisparity map 124, any suitable dense stereo algorithm may be used. Forexample, a four-plane model for dynamic programming may be used,although other graphs may be employed, such as a three-plane model, asingle plane model, and the like.

The disparity map 124 is compared to at least a portion of the kernelimage 126 to determine matching disparity values. A disparity-basedkernel image is a model or template disparity map that is comparedagainst the disparity map 124. The use of a kernel image is optional. Akernel image can be used to rapidly recover the approximate silhouetteof an object. A more precise but costly alternative, discussed in thenext paragraph, is to use optimization methods to define a binary maskof foreground vs. background points. The kernel image 126 can be anarray of pixel values which represent the stereo disparity of an objectto be located or searched for. More particularly, the kernel image 126is an encoding of the silhouette of the object to be located as well assurface shape of the object to be located, e.g., the ‘bumpiness’ ordepth of the object. In this manner, the kernel image 126 indicates the3d surface shape of the object to be located from a point of view. Thekernel image 126 can be, for example, a predetermined disparity map of ageneric torso shape or any other shape or object. The kernel image 126can be calculated in advance, or derived from a previous disparity map,or otherwise obtained. The kernel image 126 can be an approximation ofthe object that it represents, in other words, a rough model of theobject. The disparity map 124 can also be used to determine the depth ordistance of pixels relative to the stereo camera 50. An average of thesedistances (a distance to the object) can be used to scale the kernelimage 126 before disparity map 124 is searched against the kernel image126. As discussed below, color/contrast information 128, possibly from apreceding disparity map or previous stereo video frames, can be used inseparating the background.

In general, it should be noted that disparity alone can be a basis forforeground/background separation, based on the assumption that points ona foreground object are more likely to have high disparity. Pixels of aforeground object can be separated based on their degree of disparity.

Foreground/background separation can be performed by fusing astereo-based segmentation algorithm with a color/contrast basedsegmentation algorithm. Algorithms for automatically separating layersusing color/contrast or stereo alone are often prone to errors. Byfusing color/contrast analysis with stereo matching information, layerscan be inferred accurately and efficiently. A Layered DynamicProgramming (LDP) algorithm can be used to solve stereo in an extended6-state space that represents both foreground/background layers andoccluded regions. The resulting stereo-match likelihood is then fusedwith a contrast-sensitive color model that is learned on the fly, andstereo disparities are obtained by dynamic programming. A secondalgorithm, Layered Graph Cut (LGC), can be used to marginalize thestereo match likelihood over foreground and background hypotheses forfusion with a contrast-sensitive color model like the one used in LDP.Segmentation is then solved efficiently by a ternary graph cut. In sum,the device driver 78 uses one or more algorithms for fast and reliableforeground/background segregation using stereo and/or color/contrastinformation, which produces a separated foreground object 130. Foradditional details, see “Bi-layer segmentation of binocular stereovideo”, by Vladimir Kolmogorov, Antonio Criminisi, Andrew Blake,Geoffrey Cross, Carsten Rother (US Proc. IEEE Computer Vision andPattern Recognition, 2005).

The separation techniques discussed above have certain properties. Theyare robust and fast enough for real time use. They generally do notgenerate artifacts, even when the color of an object at its edge is thesame as part of the adjoining background. The techniques are able toextract a synthesized image of an object that is mostly free ofartifacts; the background is cleanly removed. A silhouette can berecovered to pixel (or even subpixel) precision, so that when therecovered foreground is superimposed on a new background, color from theold background does not leak in.

Having separated stereo images of one or more objects in a scene,different types of information about objects in a scene can then bedetermined 132. For example, different types of objects can beidentified by using different kernel images 126. If an object has beenseparated from the background, that object can be identified bycomparing it to different kernel images. Stereo-based depth informationcan also be obtained. A virtual or cyclopean image of the object can becomputed from the left and right image using ordinary geometry-basedtechniques. The location of the separated object in the stereo-basedimage and/or an input image may be indicated in any suitable manner. Forexample, the disparity data, pixel locations, or any other suitableindicator of the located object may be associated with the image asmeta-data. The image with the located object may be used by the displaymanipulator module to perform some action or it may be sent to anotherapplication. Artifacts in the generated image can be corrected using asplit-patch search algorithm, which may involve: restricting candidatepatches to those lying on corresponding (left or right) epipolar lines;constraining a search region using tight, geometric depth bounds; andapplying exemplar-based synthesis sparsely, where flagged by aninconsistency test. For further details, see “The SPS Algorithm:Patching Figural Continuity and Transparency by Split-Patch Search”, byAntonio Criminisi, Andrew Blake, (US Proc. IEEE Computer Vision andPattern Recognition, 2004). Border matting is an alternative method forcorrecting artifacts and obtaining pixel or subpixel precision. Fordetails, see V. Kolmogorov, A. Criminisi, A. Blake, G. Cross, C. Rother,Probabilistic fusion of stereo with color and contrast for bi-layersegmentation, June 2005, MSR-TR-2005-35.

It should be appreciated that stereo image analysis as discussed abovecan be repeatedly performed in real time on paired frames of the stereovideo signal. This allows real time operations such as tracking thechanging position of an object, providing accurate real time “cut out”video of an object as it moves and changes (i.e., video of an objectwith the background cleanly removed regardless of the nature of thebackground), and providing a dynamic depth map of an object as it movesor changes in real time.

FIG. 6 shows how stereo-derived object information can be used inconjunction with a game and VR engine. A stereo image pair is received150 from a stereo video signal. Using one or more techniques discussedabove, for example stereo matching segmentation fused withcolor/contrast segmentation, foreground/background separation isperformed to separate 152 one or more objects from the background.Information about the one or more objects is obtained 154, for example,depth information, a well-defined image of the object, the identity ofthe one or more objects, etc. This information is provided 156 to thegame program. The game program receives 158 the object information anduses it (some examples follow, see FIGS. 7-10) to affect or modify 160the behavior or “play” of the game, and/or the appearance of the game,or other aspects of the game. As instructed by the game program, therender engine renders 162 the game as modified 160 in accordance withthe stereo-derived object information.

FIG. 7 shows an example of how stereo-based foreground/backgroundseparation can be used to control a model or avatar 180 in a 3d game.The boxes on the left side of FIG. 7 represent real scenes 182 capturedby a stereo camera. Although for discussion the real scenes 182 areshown overhead, the real scenes 182 in practice would be captured from astereo camera with a somewhat horizontal line of sight (e.g., on top ofa television). The boxes on the right side of FIG. 7 show overhead views184 of a 3d virtual scene with a foreground model or avatar 180.Starting chronologically at the bottom of FIG. 7, at stage A, a hand 186is captured in stereo and separated from its background as discussedabove. The depth of the object, in this case the hand, is obtained. Forexample, at stage A the hand's depth may be 3 meters from the stereocamera, or, the hand's 186 depth may be measured relative to some otherreference point or stereo-recognized object such as the body, head,torso, etc. of the person whose hand 186 is being captured. The depth isused to modify the avatar model 180 by transforming the model 180 toplace the right hand and arm of the model in accordance with thedetected depth of the hand 186. Through subsequent stages B and C, asthe real hand 186 is detected to change in depth (approach the stereocamera, move away from the real body to which it is attached, etc.), theavatar model 180 is modified accordingly, thus modeling the motion ofthe hand 186. In effect, stereo-based foreground/background separationis used to control the avatar model 180. Furthermore, the avatar modelcan be checked for collision detection, for example with model 188.

It should be noted that boundary recovery to pixel precision (or better)can have allow not just determining the location of an object (e.g., “alimb”) but its precise outline, shape, and interior texture. Thus theentire shape and texture of the object can be reproduced elsewhere, andcan be subjected to transformations of color or shape or texture alongthe way.

It should be appreciated that the example of FIG. 7 involves more thanjust the use of stereo-derived depth information to control an avatar.Stereo cameras are generally useful for obtaining raw depth or distanceinformation about pixels. However, accurately identifying an object inassociation with its depth is a more complex and useful procedure. Inother words, ordinary stereo analysis may provide depth of pixels,however, mere depth information may not accurately indicate which ofthose pixels correspond to particular objects. By using a kernel image,color/contrast information, or other techniques forforeground/background separation, depth information can be provided forparticular objects, which can allow objects to be individually mapped todepth-sensitive actions or objects in a game or 3d virtual reality.

Although it is possible to continuously change a model to correspond tothe continuously changing depth of a physical object, for performancereasons, some games have only a limited or predefined set of motions oranimations for a model, whether the model is a model of a human figure,an automobile, a robot, an animal, etc. In other words, a model may havea set of predefined animations such as jumping, switching items,crouching, turning left, turning right, etc. In this case, gesturerecognition may be used rather than a direct mapping between the shapeor position of a model and the detected depth or position of an object.

FIG. 8 shows a process for using stereo foreground/background separationto recognize gestures for controlling a game. Paired stereo images areprocessed to segment 200 an object therein from its background. Again,kernel disparity maps, depth information, and color/contrast informationcan be used to accurately segment 200 the object from its background.The position of the segmented 200 object is determined, and, using aprevious location of the object, the object's motion is tracked 202. Forexample, the 3d path of a hand, an object in a hand, or a head, or abody, or any other real object can be tracked 202. The tracked motion ofthe object, which includes at least depth information, is identified 204as a particular 3d gesture. The identified 204 3d gesture then acts as atrigger to generate 206 a corresponding model motion or action, whichmight correspond to an action command in the game, for example.

Gestures can be recognized in a number of ways. For example, an object'stracked path or motion can be compared against a set of predefinedmotion templates. A predefined motion template can include information,for example, such as a 3d volume (for the motion path) divided intoordered sub-volumes, each of which must be occupied by the object, inorder, over a given range of time. If the tracked object is a handheldcylindrical object, the path of the cylindrical object could be comparedto various specific motion templates, such as a side-to-side sweepmotion template, an overhead downstroke motion template, a poke motion,etc. Whenever the continually updating recent motion path of the axematches one of its motion templates, the template's gesture isidentified 204 as having occurred, and a corresponding command isissued. Simpler gesture recognition techniques can be used. For example,movements can be mapped to basic directions and in turn correspondingdirection commands in a game. For 3d navigation, a real object can bedetected to move up, down, left, right, forward, or backward, orcombinations thereof (e.g., forward, up, and to the left), and acorresponding movement command may be issued in the game. In otherwords, stereo-based foreground/background separation can be combinedwith depth information to generate three-dimensional direction commands.

FIG. 9 shows an example of mapping a separated image of a foregroundphysical object to a model that is then rendered and displayed. Theboxes 230 in FIG. 9 represent a real world scene as seen by a stereocamera, in this case, a person's torso in a room. An image of an objectis extracted 232 from stereo images of a scene using techniquesdiscussed above. For example, a kernel disparity image of the rough formof a human torso can be used for foreground/background separation,possibly in conjunction with other techniques. In one embodiment, theextracted image can include depth values of the pixels of the image. Inother words, a 3d image of the detected object. In the example of FIG.9, by keying on facial features, the extracted image is processedfurther to obtain a particular portion of the object—the face. Theoriginal or the refined images 234 can be normalized so that the edgepixels have a depth of zero. In the example, an image of the face couldalso be obtained from a suitable face-like kernel image.

Because an image of the extracted object is going to be used in a 3dgame or virtual reality, the extracted image 234 may be further prepared236 for 3d rendering. For example, the image 234 may be rescaled orre-dimensioned. The image 234 may be converted into a bump map or adisplacement map. Other operations can be used. For example, the colorof the image may be adjusted to match the 3d scene that it will appearin. Finally, in one embodiment, the image is mapped 238 to a 3d model240. This can involve texture mapping the color values of the pixels, orusing the depths of the pixels to displace vertices of the model 240(i.e., displacement mapping), or mapping a bump map of the image to themodel 240. In one embodiment, the image's 3d depth values are not usedand the color values of the pixels are mapped to the surface of themodel 240. In another embodiment, only the depth values are mapped tothe model 240. Furthermore, if a displacement or bump map is used,processing time may be too high for updating the model 240 in real timeto match changes in the scene, and the mapping 238 may occur only onceduring an initialization stage. However, in a preferred embodiment theentire process is repeated in real time so that frames of the 3d gameare rendered to match changes in the scene in real time as captured bythe stereo camera. In either case, renderings 242 are based on images ofan object obtained using stereo-based foreground/background separation.

In another embodiment, the extracted image of the object is not mapped238 to a model. Techniques for stereo-based foreground/backgroundseparation have advanced to the point where foreground images can beseparated cleanly and efficiently, even if the background has a samecolor as the object in the foreground. Furthermore, the images can beseparated and synthesized in such a manner that the images aresignificantly free of artifacts. In other words, an accurate profile ofthe object can be obtained; the background is accurately removedindependent of the nature of the background. Extracted images usuallyhave a quality comparable to images obtained using blue or green screenseparation; the images are sharp and accurate representations of theobject. Therefore, an image of an object can be displayed directly in agame or 3d virtual reality, either as a planar surface, or as a 3dsurface, possibly with some modeled “backing” to allow 3d non-frontalviewing.

In another embodiment, the extracted image is co-displayed with the 3dvirtual reality, but is not incorporated into the 3d virtual reality.For example, if a number of players are participating in a same 3dvirtual reality (each with a stereo camera), each player's “heads updisplay” (user interface) may include images or real time video of thehead/torso of each participant. The general idea of using stereotechniques to extract foreground images cleanly separated from thebackground and immersing the images in a game can take other forms. Forexample, extracted images or video can be displayed as two-dimensionalimages, whether in a two-dimensional game or a three-dimensional game.As another example, extracted images could be displayed in a virtualmonitor (within the game) or an instant-messenger type of application(within the game or as part of the game interface). A remote partner orcombatant can be seen, in some form, within scenes in a game.

In another embodiment, a game is provided with artificial intelligencefor recognizing facial gestures of stereo-extracted face images. Thisinformation can be incorporated into a game in any number of ways.Artificial-intelligence game characters can be programmed to respondaccording to a player's facial gesture, for example, respondingpositively to a smiling face, or responding negatively to a frowning orangry face.

Stereo-based foreground/background separation is also useful for objectrecognition. FIG. 10 shows how stereo-based object recognition can beused for 3d gaming. As discussed above, the stereo video signal can besearched for kernel images of different types of objects, thusperforming a form of object detection or recognition; if a kernel imageis matched to a portion of a captured scene, the object associated withthat kernel image is deemed to be present in the scene. Consider anexample where there are three kernel images (not shown) to be searchedfor: a kernel image of a briefcase; a kernel image of a flashlight orcylindrical object; and a kernel image of an arm/hand holding nothing.In this example, the game is a type where the player controls a 3davatar, character, vehicle, etc. that is rendered and displayed. In afirst physical scene 260 A, a real person is holding a briefcase. One ormore pairs of stereo frames are processed to recognize 262 the object(e.g., “a briefcase”).

In response to the recognition 262, the game causes the 3d character to“hold” a corresponding virtual object such as a virtual briefcase. Theholding of the object can simply be implemented as a change to the stateof the character (e.g., a flag is set indicating that the virtual objectis currently being held) without any corresponding change in what isdisplayed or rendered. Additionally or alternatively, the virtualholding can be implemented by causing the 3d character to be rendered toappear to hold a virtual object associated with the matched kernelimage, as seen in rendered characters 264. Similarly, in scene 260 B, aflashlight is recognized 262 and the game character is modified and/orrendered accordingly. If the recognizing 262 is handedness sensitive,then if the flashlight is in the same hand as the briefcase was, thecharacter is made to stop holding the virtual briefcase, or if theflashlight is in the real person's other hand, then the character mightbe made to virtually hold both virtual objects. In scene 260 C, an emptyarm/hand is recognized and the game character is rendered accordingly.In this manner, a person with a set of real objects can control theobjects virtually held by a game character by picking up any of thecorresponding real objects. Real objects held in a hand can berecognized by using both the kernel image of the arm/hand and the kernelimages of the other objects to detect which object is currently in ahand of the person. As mentioned earlier, kernel disparity images can beobtained in advance (e.g., part of the content embedded in a particulargame), or during a training process where an object is held in front ofthe stereo camera, or from disparity maps extracted from earlierprocessed scenes.

Other objects can be recognized. For example, clothes, hats, etc. wornby a real person can be recognized and similarly translated into the 3dvirtual reality. Even large articles or props such as bicycles,furniture, etc. can be recognized with similar effect.

In general, it has been shown how game consoles and 3d virtual realitysystems can benefit from a richer set of visual control information andthe addition of real-time information, including video, of objects.Stereo video processing can be used to improve a game system, forexample by providing more natural control, providing real-time imagesfor importation or translation into a 3d virtual reality, and so on.Embodiments relating to immersing or displaying stereo-extracted imagesof foreground objects into 3d games or virtual realities can also beapplied in 2d games, the broader idea being immersion into computergenerated graphical environments.

In conclusion, those skilled in the art will realize that storagedevices used to store program instructions can be distributed across anetwork. For example a remote computer may store an example of a processdescribed as software. A local or terminal computer may access theremote computer and download a part or all of the software to run theprogram. Alternatively the local computer may download pieces of thesoftware as needed, or distributively process by executing some softwareinstructions at the local terminal and some at the remote computer (orcomputer network). Those skilled in the art will also realize that byutilizing conventional techniques known to those skilled in the art, allor a portion of the software instructions may be carried out by adedicated circuit, such as a DSP, programmable logic array, or the like.

All of the embodiments and features discussed above can be realized inthe form of information stored in volatile or non-volatile computer ordevice readable medium. This is deemed to include at least media such asCD-ROM, magnetic media, flash ROM, etc., storing machine executableinstructions, or source code, or any other information that can be usedto enable or configure computing devices to perform the variousembodiments discussed above. This is also deemed to include at leastvolatile memory such as RAM storing information such as CPU instructionsduring execution of a program carrying out an embodiment, as well asnon-volatile media storing information that allows a program orexecutable to be loaded and executed.

1. A method for producing a video sequence comprising: receiving stereoimages of a captured scene with a physical foreground object and aphysical background; using a first disparity map to generate a kernelimage, the kernel image comprising an array of pixel values representinga stereo disparity of an object to be located; scaling the kernel imageusing a second disparity map, the scaling based on at least a distanceof a corresponding portion of the object relative to a stereo camerathat provided the stereo images; performing, in real-time, aforeground/background separation algorithm on the stereo images, theseparation algorithm configured compute differences between the receivedstereo images and stores the differences as a third disparity map;comparing the third disparity map to at least a portion of the scaledkernel image to identify pixels of the stereo images that represent thephysical foreground object; and providing the identified pixels thatrepresent the physical foreground object to at least one of a twodimensional and a three dimensional game.
 2. The method of claim 1, thepixels forming borders that substantially correspond to respectivephysical profiles of the physical foreground object.
 3. The method ofclaim 2, the comparison of the third disparity map to at least a portionof the scaled kernel image configured to identify the pixels for anyphysical background comprising arbitrary and substantially non-uniformcolors.
 4. The method of claim 2, one or more borders having a portioncorresponding to a portion of the physical foreground object thatpartially obscures a portion of the physical background that has a samecolor as the obscuring portion of the physical foreground object.
 5. Themethod of claim 2, the foreground/background separation algorithmconfigured to use at least one of stereo disparity, stereo matching, anda color of pixels from frames of a stereo video signal.
 6. The method ofclaim 1, the foreground/background separation algorithm comprisingobtaining a stereo-match likelihood and fusing it with acontrast-sensitive color model.
 7. The method of claim 1, a model in a3d virtual reality is at least one of moved and reoriented in accordancewith changes in at least one of location and orientation of the physicalforeground object as determined based on the identified pixels.
 8. Themethod of claim 1, the method comprising using the identified pixels todetermine at least one of a 3d location and an orientation of thephysical foreground object relative to the stereo camera and at leastone of locating and orienting a 3d model in accordance with at least oneof the 3d location and the orientation of the physical foregroundobject.
 9. The method of claim 1, depth values of the pixels aredetermined based upon the comparison and are used for controlling a 3dvirtual reality in the game.
 10. The method of claim 9, the depth valuesare used to control at least one of movement and orientation of at leastone of a model and viewpoint in the 3d virtual reality.
 11. The methodof claim 1, comprising, based upon the identified pixels, mappingmotions of the physical foreground object to predefined commands used tocontrol a 3d virtual reality in the game.
 12. The method of claim 1,pixels captured from a real-time stereo video signal that represent thephysical foreground object are identified in the absence of color andstereo-matching information.
 13. The method of claim 1, comprisingcorrecting for at least one artifact in at least one identified pixel ofthe physical foreground object.
 14. The method of claim 13, correctingfor the at least one artifact in the at least one identified pixel ofthe physical foreground object comprising using a split-patch searchalgorithm.
 15. The method of claim 1, the foreground/backgroundseparation algorithm is configured to: obtain a stereo-match likelihoodusing a layered dynamic programming algorithm configured to solve stereoin an extended 6-state space representing at least oneforeground-background layer and one occluded region; use a layered graphcut algorithm to marginalize the obtained stereo-match likelihood overforeground and background hypotheses; and fuse the obtained stereo-matchlikelihood with a contrast-sensitive color model.
 16. A computerreadable storage device configured to store computer executableinstructions for enabling an apparatus to perform a method, the methodcomprising: receiving stereo images of a captured scene with a physicalforeground object and a physical background; using a first disparity mapto generate a kernel image, the kernel image comprising an array ofpixel values representing a stereo disparity of an object to be located;scaling the kernel image using a second disparity map, the scaling basedon at least a distance of a corresponding portion of the object relativeto a stereo camera that provided the stereo images; performing, inreal-time, a foreground/background separation algorithm on the stereoimages, the separation algorithm configured to compute differencesbetween the received stereo images and stores the differences as a thirddisparity map; comparing the third disparity map to at least a portionof the scaled kernel image to identify pixels of the stereo images thatrepresent the physical foreground object; and providing the identifiedpixels that represent the physical foreground object to at least one ofa two dimensional and a three dimensional game.
 17. The computerreadable storage device of claim 16, the identified pixels formingborders that correspond to, with at least pixel level accuracy, physicalprofiles of the physical foreground object.
 18. The computer readablestorage device of claim 17, the comparison of the third disparity map toat least a portion of the scaled kernel image configured to identify thepixels for any physical background comprising arbitrary andsubstantially non-uniform colors.
 19. The computer readable storagedevice of claim 17, one or more borders having a portion correspondingto a portion of the physical foreground object that only partiallyobscures a portion of the physical background that has a same color asthe obscuring portion of the physical foreground object.
 20. Thecomputer readable storage device of claim 16, the foreground/backgroundseparation algorithm comprising obtaining a stereo-match likelihood andfusing it with a contrast-sensitive color model.
 21. The computerreadable storage device of claim 16, the game comprising a 3d virtualreality, and a model in the 3d virtual reality is at least one of movedand reoriented in accordance with changes in at least one of locationand orientation of the physical foreground object as determined based onthe identified pixels representing the physical foreground object. 22.The computer readable storage device of claim 16, the method comprisingusing the identified pixels to determine at least one of a 3d locationand an orientation of the physical foreground object relative to thestereo camera that provided the stereo images and at least one oflocating and orienting a 3d model in accordance with at least one of the3d location and the orientation of the physical foreground object. 23.The computer readable storage device of claim 16, comprising, based uponthe identified pixels, mapping motions of the physical foreground objectto predefined commands used to control the game.
 24. The computerreadable storage device of claim 16, depth values are determined basedupon the comparison and are used for controlling the game.
 25. Thecomputer readable storage device of claim 24, the depth values are usedto control at least one of movement and orientation of at least one of amodel and a viewpoint in the game.
 26. The computer readable storagedevice of claim 16, the apparatus comprises a game console.
 27. Acomputer comprising a microprocessor configured to execute a methodstored on a computer readable storage device, the method comprising:receiving stereo images of a captured scene with a physical foregroundobject and a physical background; using a first disparity map togenerate a kernel image, the kernel image comprising an array of pixelvalues representing a stereo disparity of an object to be located;scaling the kernel image using a second disparity map, the scaling basedon at least a distance of a corresponding portion of the object relativeto a stereo camera that provided the stereo images; performing, inreal-time, a foreground/background separation algorithm on the stereoimages, the separation algorithm configured to compute differencesbetween the received stereo images and store the differences as a thirddisparity map; comparing the third disparity map to at least a portionof the scaled kernel image to identify pixels of the stereo images thatrepresent the physical foreground object; and providing the identifiedpixels that represent the physical foreground object to at least one ofa two dimensional and a three dimensional game.